def update(self,frame,recent_pupil_positions,events):
        """
        gets called once every frame.
        reference positon need to be published to shared_pos
        if no reference was found, publish 0,0
        """
        if self.active:

            img  = frame.img

            if self.world_size is None:
                self.world_size = img.shape[1],img.shape[0]

            self.candidate_ellipses = get_canditate_ellipses(img,
                                                            area_threshold=self.area_threshold.value,
                                                            dist_threshold=self.dist_threshold.value,
                                                            min_ring_count=3,
                                                            visual_debug=self.show_edges.value)

            if len(self.candidate_ellipses) > 0:
                self.detected = True
                marker_pos = self.candidate_ellipses[0][0]
                self.pos = normalize(marker_pos,(img.shape[1],img.shape[0]),flip_y=True)


            else:
                self.detected = False
                self.pos = None #indicate that no reference is detected


            # center dark or white?
            if self.detected:
                second_ellipse =  self.candidate_ellipses[1]
                col_slice = int(second_ellipse[0][0]-second_ellipse[1][0]/2),int(second_ellipse[0][0]+second_ellipse[1][0]/2)
                row_slice = int(second_ellipse[0][1]-second_ellipse[1][1]/2),int(second_ellipse[0][1]+second_ellipse[1][1]/2)
                marker_roi = img[slice(*row_slice),slice(*col_slice)]
                marker_gray = cv2.cvtColor(marker_roi,cv2.COLOR_BGR2GRAY)
                avg = cv2.mean(marker_gray)[0]
                center = marker_gray[second_ellipse[1][1]/2,second_ellipse[1][0]/2]
                rel_shade = center-avg

                #auto_stop logic
                if rel_shade > 30:
                    #bright marker center found
                    self.auto_stop +=1
                    self.stop_marker_found = True

                else:
                    self.auto_stop = 0
                    self.stop_marker_found = False


            #tracking logic
            if self.detected and not self.stop_marker_found:
                # calculate smoothed manhattan velocity
                smoother = 0.3
                smooth_pos = np.array(self.smooth_pos)
                pos = np.array(self.pos)
                new_smooth_pos = smooth_pos + smoother*(pos-smooth_pos)
                smooth_vel_vec = new_smooth_pos - smooth_pos
                smooth_pos = new_smooth_pos
                self.smooth_pos = list(smooth_pos)
                #manhattan distance for velocity
                new_vel = abs(smooth_vel_vec[0])+abs(smooth_vel_vec[1])
                self.smooth_vel = self.smooth_vel + smoother*(new_vel-self.smooth_vel)

                #distance to last sampled site
                sample_ref_dist = smooth_pos-np.array(self.sample_site)
                sample_ref_dist = abs(sample_ref_dist[0])+abs(sample_ref_dist[1])

                # start counter if ref is resting in place and not at last sample site
                if not self.counter:
                    if self.smooth_vel < 0.01 and sample_ref_dist > 0.1:
                        self.sample_site = self.smooth_pos
                        audio.beep()
                        logger.debug("Steady marker found. Starting to sample %s datapoints" %self.counter_max)
                        self.counter = self.counter_max

                if self.counter:
                    if self.smooth_vel > 0.01:
                        audio.tink()
                        logger.debug("Marker moved to quickly: Aborted sample. Sampled %s datapoints. Looking for steady marker again."%(self.counter_max-self.counter))
                        self.counter = 0
                    else:
                        self.counter -= 1
                        ref = {}
                        ref["norm_pos"] = self.pos
                        ref["timestamp"] = frame.timestamp
                        self.ref_list.append(ref)
                        if self.counter == 0:
                            #last sample before counter done and moving on
                            audio.tink()
                            logger.debug("Sampled %s datapoints. Stopping to sample. Looking for steady marker again."%self.counter_max)


            #always save pupil positions
            for p_pt in recent_pupil_positions:
                if p_pt['norm_pupil'] is not None:
                    self.pupil_list.append(p_pt)



            #stop if autostop condition is satisfied:
            if self.auto_stop >=self.auto_stop_max:
                self.auto_stop = 0
                self.stop()


        else:
            pass
Ejemplo n.º 2
0
    def update(self,frame,recent_pupil_positions,events):

        #get world image size for error fitting later.
        if self.world_size is None:
            self.world_size = frame.img.shape[1],frame.img.shape[0]
            self.res.value = np.sqrt(self.world_size[0]**2+self.world_size[1]**2)

        if self.window_should_close:
            self.close_window()

        if self.window_should_open:
            self.open_window()

        if self.active:
            img = frame.img

            #detect the marker
            self.candidate_ellipses = get_canditate_ellipses(img,
                                                            area_threshold=self.area_threshold.value,
                                                            dist_threshold=self.dist_threshold.value,
                                                            min_ring_count=4,
                                                            visual_debug=self.show_edges.value)

            if len(self.candidate_ellipses) > 0:
                self.detected= True
                marker_pos = self.candidate_ellipses[0][0]
                self.pos = normalize(marker_pos,(img.shape[1],img.shape[0]),flip_y=True)

            else:
                self.detected = False
                self.pos = None #indicate that no reference is detected


            #only save a valid ref position if within sample window of calibraiton routine
            on_position = 0 < self.screen_marker_state < self.screen_marker_max-50
            if on_position and self.detected:
                ref = {}
                ref["norm_pos"] = self.pos
                ref["timestamp"] = frame.timestamp
                ref['site'] = self.active_site
                self.ref_list.append(ref)

            #always save pupil positions
            for p_pt in recent_pupil_positions:
                if p_pt['norm_gaze'] is not None:
                    self.gaze_list.append(p_pt)

            # Animate the screen marker
            if self.screen_marker_state < self.screen_marker_max:
                if self.detected or not on_position:
                    self.screen_marker_state += 1
            else:
                self.screen_marker_state = 0
                self.active_site += 1
                logger.debug("Moving screen marker to site no %s"%self.active_site)
                if self.active_site == len(self.sites)-2:
                    self.stop()
                    return

            # function to smoothly interpolate between points input:(0-screen_marker_max) output: (0-1)
            m, s = self.screen_marker_max, self.screen_marker_state

            interpolation_weight = np.tanh(((s-2/3.*m)*4.)/(1/3.*m))*(-.5)+.5

            #use np.arrays for per element wise math
            current = np.array(self.sites[self.active_site])
            next = np.array(self.sites[self.active_site+1])
            # weighted sum to interpolate between current and next
            new_pos =  current * interpolation_weight + next * (1-interpolation_weight)
            #broadcast next commanded marker postion of screen
            self.display_pos = list(new_pos)
            self.on_position = on_position
Ejemplo n.º 3
0
    def update(self,frame,recent_pupil_positions,events):
        if self.window_should_close:
            self.close_window()

        if self.window_should_open:
            self.open_window()

        if self.active:
            img = frame.img

            #get world image size for error fitting later.
            if self.world_size is None:
                self.world_size = img.shape[1],img.shape[0]

            #detect the marker
            self.candidate_ellipses = get_canditate_ellipses(img,
                                                            area_threshold=self.area_threshold.value,
                                                            dist_threshold=self.dist_threshold.value,
                                                            min_ring_count=4,
                                                            visual_debug=self.show_edges.value)

            if len(self.candidate_ellipses) > 0:
                self.detected= True
                marker_pos = self.candidate_ellipses[0][0]
                self.pos = normalize(marker_pos,(img.shape[1],img.shape[0]),flip_y=True)

            else:
                self.detected = False
                self.pos = None #indicate that no reference is detected


            #only save a valid ref position if within sample window of calibraiton routine
            on_position = 0 < self.screen_marker_state < self.screen_marker_max-50
            if on_position and self.detected:
                ref = {}
                ref["norm_pos"] = self.pos
                ref["timestamp"] = frame.timestamp
                self.ref_list.append(ref)

            #always save pupil positions
            for p_pt in recent_pupil_positions:
                if p_pt['norm_pupil'] is not None:
                    self.pupil_list.append(p_pt)

            # Animate the screen marker
            if self.screen_marker_state < self.screen_marker_max:
                if self.detected or not on_position:
                    self.screen_marker_state += 1
            else:
                self.screen_marker_state = 0
                self.active_site += 1
                logger.debug("Moving screen marker to site no %s"%self.active_site)
                if self.active_site == 10:
                    self.stop()
                    return

            # function to smoothly interpolate between points input:(0-screen_marker_max) output: (0-1)
            m, s = self.screen_marker_max, self.screen_marker_state

            interpolation_weight = np.tanh(((s-2/3.*m)*4.)/(1/3.*m))*(-.5)+.5

            #use np.arrays for per element wise math
            current = np.array(self.sites[self.active_site])
            next = np.array(self.sites[self.active_site+1])
            # weighted sum to interpolate between current and next
            new_pos =  current * interpolation_weight + next * (1-interpolation_weight)
            #broadcast next commanded marker postion of screen
            self.display_pos = list(new_pos)
            self.on_position = on_position
    def update(self, frame, recent_pupil_positions, events):
        """
        gets called once every frame.
        reference positon need to be published to shared_pos
        if no reference was found, publish 0,0
        """
        if self.active:

            img = frame.img

            if self.world_size is None:
                self.world_size = img.shape[1], img.shape[0]

            self.candidate_ellipses = get_canditate_ellipses(
                img,
                area_threshold=self.area_threshold.value,
                dist_threshold=self.dist_threshold.value,
                min_ring_count=5,
                visual_debug=self.show_edges.value)

            if len(self.candidate_ellipses) > 0:
                self.detected = True
                marker_pos = self.candidate_ellipses[0][0]
                self.pos = normalize(marker_pos, (img.shape[1], img.shape[0]),
                                     flip_y=True)

            else:
                self.detected = False
                self.pos = None  #indicate that no reference is detected

            # center dark or white?
            if self.detected:
                second_ellipse = self.candidate_ellipses[1]
                col_slice = int(second_ellipse[0][0] - second_ellipse[1][0] /
                                2), int(second_ellipse[0][0] +
                                        second_ellipse[1][0] / 2)
                row_slice = int(second_ellipse[0][1] - second_ellipse[1][1] /
                                2), int(second_ellipse[0][1] +
                                        second_ellipse[1][1] / 2)
                marker_roi = img[slice(*row_slice), slice(*col_slice)]
                marker_gray = cv2.cvtColor(marker_roi, cv2.COLOR_BGR2GRAY)
                avg = cv2.mean(marker_gray)[0]
                center = marker_gray[second_ellipse[1][1] / 2,
                                     second_ellipse[1][0] / 2]
                rel_shade = center - avg

                #auto_stop logic
                if rel_shade > 30:
                    #bright marker center found
                    self.auto_stop += 1
                    self.stop_marker_found = True

                else:
                    self.auto_stop = 0
                    self.stop_marker_found = False

            #tracking logic
            if self.detected and not self.stop_marker_found:
                # calculate smoothed manhattan velocity
                smoother = 0.3
                smooth_pos = np.array(self.smooth_pos)
                pos = np.array(self.pos)
                new_smooth_pos = smooth_pos + smoother * (pos - smooth_pos)
                smooth_vel_vec = new_smooth_pos - smooth_pos
                smooth_pos = new_smooth_pos
                self.smooth_pos = list(smooth_pos)
                #manhattan distance for velocity
                new_vel = abs(smooth_vel_vec[0]) + abs(smooth_vel_vec[1])
                self.smooth_vel = self.smooth_vel + smoother * (
                    new_vel - self.smooth_vel)

                #distance to last sampled site
                sample_ref_dist = smooth_pos - np.array(self.sample_site)
                sample_ref_dist = abs(sample_ref_dist[0]) + abs(
                    sample_ref_dist[1])

                # start counter if ref is resting in place and not at last sample site
                if not self.counter:
                    if self.smooth_vel < 0.01 and sample_ref_dist > 0.1:
                        self.sample_site = self.smooth_pos
                        audio.beep()
                        logger.debug(
                            "Steady marker found. Starting to sample %s datapoints"
                            % self.counter_max)
                        self.counter = self.counter_max

                if self.counter:
                    if self.smooth_vel > 0.01:
                        audio.tink()
                        logger.debug(
                            "Marker moved to quickly: Aborted sample. Sampled %s datapoints. Looking for steady marker again."
                            % (self.counter_max - self.counter))
                        self.counter = 0
                    else:
                        self.counter -= 1
                        ref = {}
                        ref["norm_pos"] = self.pos
                        ref["timestamp"] = frame.timestamp
                        self.ref_list.append(ref)
                        if self.counter == 0:
                            #last sample before counter done and moving on
                            audio.tink()
                            logger.debug(
                                "Sampled %s datapoints. Stopping to sample. Looking for steady marker again."
                                % self.counter_max)

            #always save pupil positions
            for p_pt in recent_pupil_positions:
                if p_pt['norm_pupil'] is not None:
                    self.pupil_list.append(p_pt)

            #stop if autostop condition is satisfied:
            if self.auto_stop >= self.auto_stop_max:
                self.auto_stop = 0
                self.stop()

        else:
            pass